Chemical Composition and <i>In Vitro</i> Digestibility of Whole‐Crop Pea and Pea–Cereal Mixture Silages Grown in South‐western Quebec
Bibliographic record
Abstract
Abstract The objective of this study was to determine the chemical composition and in vitro dry matter (IVDMD) and neutral detergent fibre (IVNDFD) digestibilities of silages made from whole‐crop pea [Pisum sativum L. (PS)], pea–wheat [Triticum aestivum L. (PW)], pea–barley [Hordeum vulgare L. (PB)] and pea–oat [Avena sativa L. (PO)] mixtures harvested 8 weeks (H8) and 10 weeks (H10) after seeding. Forty‐five days after ensiling, all forages were well ensiled as indicated by low pH and low water‐soluble carbohydrate content and high lactic acid concentration. Regardless of forage type, crude protein (CP) and IVNDFD were higher while starch and acid detergent lignin were lower in H8 than H10. However, harvest date had no effect on neutral (NDF) and acid (ADF) detergent fibre of the silages. Within each harvest date, CP was higher while NDF was lower for PS than pea–cereal silages. Differences in CP and fibre fractions between the pea–cereal mixture silages were not consistent for the two harvest dates. The IVDMD of PS was higher than that of the three pea–cereal mixture silages in H8 but was only higher than that of PB in H10. For the pea–cereal mixtures, IVDMD was higher for PO than PB and PW in H8 and was higher for PB than PW in H10. It was concluded that silage from pea monoculture had similar forage yields and a generally higher nutritive value than silages from pea–cereal mixtures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".